A differential evolution algorithm for lot-streaming flow shop scheduling problem

Authors:
Hongyan Sang;Liang Gao;Xinyu Li
Affiliations:
State Key Lab. of Digital Manufacturing Equipment & Technology, Huazhong University of Science & Technology, Wuhan, P.R. China;State Key Lab. of Digital Manufacturing Equipment & Technology, Huazhong University of Science & Technology, Wuhan, P.R. China;State Key Lab. of Digital Manufacturing Equipment & Technology, Huazhong University of Science & Technology, Wuhan, P.R. China
Venue:
ICIC'11 Proceedings of the 7th international conference on Advanced Intelligent Computing
Year:
2011

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Abstract

A differential evolution (DE) algorithm is proposed to minimize the total weighted tardiness and earliness penalties for lot-streaming flow shop scheduling problems. In the proposed DE algorithm, the largest position value (LPV) rule is used to convert a real-number DE vector to a job permutation. The DE evolution is used to perform global exploitation, and a local search procedure is used to enhance the exploration capability. Extensive computational simulations and comparisons are provided, which demonstrate the effectiveness of the proposed DE algorithm.